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January 19, 2022

Brand DNA: The Key to a Strong Security Posture

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19
Jan 2022
Learn how AI can enhance security measures by detecting malicious assets, and safeguarding against vulnerabilities. Stay secure with advanced technology.

The internet is huge and is expanding every day. While this has many positives for businesses, managing the potential risks in this environment can be daunting. The reality is that across the internet brands are susceptible to everything from brand abuse to phishing websites. So, how is it possible that organisations can keep track of the web-based assets that belong to them, and at the same time distinguish them from something that may only look like it’s theirs? Finding and verifying all of a company’s web assets across the entire internet is a massive undertaking. You essentially need to filter the whole internet and try to pick out what is relevant, and then set about detecting the risks – or even potential risks – within what you have found.

This isn’t a process that can be managed manually. The staff-hours alone would make this hugely prohibitive, and that’s without taking into account the potential margin for error. Instead, it requires a different approach, one based around automation. At Darktrace, my team and I work on exactly those kind of solutions. We’ve developed our own algorithms to define what distinguishes a client’s brand-owned site from everything else on the internet. We refer to that as a company’s Brand DNA. These special characteristics help us to predict and identify where any brand-related assets are across the entire internet, and how they should be investigated further. The concept of an organisation’s Brand DNA breaks down into two areas: what is unique by design and what is uniqueby comparison.

Unique by Design

All brands have different design elements that help set them apart from other brands. This can be everything from their name and logo, to the different fonts and colours they use in all their communications and websites. By ingesting this data into our algorithms we are able to scan the internet for any web-based assets that may be relevant to a company, based on these key brand elements. While the elements of ‘unique by design’ are relatively easily understandable by humans, no organisations want to have their time taken up manually searching through millions of images every day in order to help them locate the web properties that might belong to their organisation.

Unique by Comparison

Conversely, ‘unique by comparison’ focuses more on the elements that a human would probably not be able to figure out by themselves. As we suggest potential new domains to customers, we build up a pool of assets. Automation allows us to find patterns in these assets that might not be immediately obvious to humans, such as elements of metadata,nameserver details, or even where a website is hosted. Although unique by design is more about what you actually see on a website and unique by comparison focuses on the back-end, in reality there are overlaps and the two things feed into each other.

As a very basic example: if a domain is hosted on nameserver where other company assets are hosted, AND the company logo is on the page, then the chances are this domain is a company-owned asset. In effect, the two approaches strengthen each other. By analysing all these details together, our algorithms can increasingly accurately score how likely an asset is to be owned by a company. I should add here that unique by comparison is based on comparing a lot of features at once, so it is often not as clear cut as the above example.

Combining Humans and AI

Ultimately, automating the process in this way helps to create a minimal-touch process for companies. The algorithms do all the filtering, enabling the creation of a much-reduced list of assets for the company to look through. Basically, we’re able to break down that list to avery small percentage of the internet that they actually need to look at and then analyse the risk those assets poseto the organisation.

We also use something which we internally label “AI2”(artificial intelligence with analyst interaction). This essentially means we’re adding a human layer to the automated process, for both input and output checks. While the algorithms do all the heavy lifting and aid scalability, the human element allows us to finetune or dive deeper into certain automated findings.

Detecting Malicious Assets

While the algorithms are principally focused on establishing a brand’s attack surface, a useful byproduct is that they can also locate malicious assets, such as potential phishing sites. For example, if something looks like it belongs to the customer, but doesn’t actually belong inside their directdigital infrastructure, then clearly there is an increased likelihood that it is either a brand abuse or phishing site.

On top of this, as part of our search process we can also automatically create combinations of possible URLs that cover common search errors such as typos or “fat finger”errors within brand names, and then hunt for those – clearly the likelihood of these URLs being rogue sites is greatly enhanced.

The Clearest View of the Attack Surface

By combining all these elements, companies are able to get the most complete view of their potential attack surface.And with the use of enhanced automation techniques they can do so with minimum effort. From this position companies are able to easily and quickly home in on the genuine items, and the areas that pose them the most risk. They can then use the resulting list to form the foundations from which they can apply the rest of their security strategy.

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
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Willem Van Zwieten
Data Science & Analytics Lead
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OT

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April 4, 2025

Darktrace Named as Market Leader in the 2025 Omdia Market Radar for OT Cybersecurity Platforms

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We are pleased to announce that Darktrace / OT has been named a Market Leader in Omdia’s  2025 Market Radar for OT Cybersecurity Platforms. We believe this highlights our unique capabilities in the OT security market and follows similar recognition from Gartner who recently named Darktrace / OT as the sole Visionary in in the Magic Quadrant for Cyber Physical Systems (CPS) Protection Platforms market.

Historically, IT and OT systems have been managed separately, creating challenges due to the differences of priorities between the two domains. While both value availability, IT emphasizes confidentiality and integrity whereas OT focuses on safety and reliability. Organizations are increasingly converging these systems to reap the benefits of automation, efficiency, and productivity (1).

Omdia’s research highlights that decision makers are increasingly prioritizing comprehensive security coverage, centralized management, and advanced cybersecurity capabilities when selecting OT security solutions (1).

Rising productivity demands have driven the convergence of OT, IT, and cloud-connected systems, expanding attack surfaces and exposing vulnerabilities. Darktrace / OT provides a comprehensive OT security solution, purpose-built for critical infrastructure, offering visibility across OT, IoT, and IT assets, bespoke risk management, and industry-leading threat detection and response powered by Self-Learning AITM.

Figure 1: Omdia vendor overview for OT cybersecurity platforms
Figure 1: Omdia vendor overview for OT cybersecurity platforms

An AI-first approach to OT security  

Many OT security vendors have integrated AI into their offerings, often leveraging machine learning for anomaly detection and threat response. However, only a few have a deep-rooted history in AI, with longstanding expertise shaping their approach beyond surface-level adoption.

The Omdia Market Radar recognizes that Darktrace has extensive background in the AI space:

“Darktrace has invested extensively in AI research to fuel its capabilities since 2013 with 200-plus patent applications, providing anomaly detection with a significant level of customization, helping with SOC productivity and efficiency, streamlining to show what matters for OT.” (1)

Unlike other security approaches that rely on existing threat data, Darktrace / OT achieves this through Self-Learning AI that understands normal business operations, detecting and containing known and unknown threats autonomously, thereby reducing Sec Ops workload and ensuring minimal downtime

This approach extends to incident investigations where an industry-first Cyber AI AnalystTM automatically investigates all relevant threats across IT and OT, prioritizes critical incidents, and then summarizes findings in an easily understandable view—bringing production engineers and security analysts together to communicate and quickly take appropriate action.

Balancing autonomous response with human oversight

In OT environments where uptime is essential, autonomous response technology can be approached with apprehension. However, Darktrace offers customizable response actions that can be set to “human confirmation mode.”

Omdia recognizes that our approach provides customizable options for autonomous response:

“Darktrace’s autonomous response functionality enforces normal, expected behavior. This can be automated but does not need to be from the beginning, and it can be fine-tuned. Alternative step-by-step mitigations are clearly laid out step-by-step and updated based on organizational risk posture and current level of progress.” (1)

This approach allows security and production to keep humans-in-the-loop with pre-defined actions for potential attacks, enforcing normal to contain a threat, and allowing production to continue without disruption.  

Bespoke vulnerability and risk management

In the realm of OT security, asset management takes precedent as one of the key focus points for organizations. With a large quantity of assets to manage, practitioners are overwhelmed with information with no real way to prioritize or apply them to their unique environment.

Darktrace / OT is recognized by Omdia as having:

“Advanced risk management capabilities that showcase metrics on impact, exploit difficulty, and estimated cost of an attack […] Given the nascency of this capability (April 2024), it is remarkably granular in depth and insight.” (1)

Enabling this is Darktrace’s unique approach to AI extends to risk management capabilities for OT. Darktrace / OT understands customers’ unique risks by building a comprehensive and contextualized picture that goes beyond isolated CVE scoring. It combines attack path modeling with MITRE ATT&CK  techniques to provide hardening recommendations regardless of patching availability and gives you a clearer view of the potential impact of an attack from APT groups.

Modular, scalable security for industrial environments

Organizations need flexibility when it comes to OT security, some want a fully integrated IT-OT security stack, while others prefer a segregated approach due to compliance or operational concerns. The Darktrace ActiveAI Security Platform offers integrated security across multiple domains, allowing flexibility and unification across IT and OT security. The platform combines telemetry from all areas of your digital estate to detect and respond to threats, including OT, network, cloud, email, and user identities.

Omdia recognizes Darktrace’s expansive coverage across multiple domains as a key reason why organizations should consider Darktrace / OT:

“Darktrace’s modular and platform, approach offer’s integrated security across multiple domains. It offers the option of Darktrace / OT as a separate platform product for those that want to segregate IT and OT cybersecurity or are not yet in a position to secure both domains in tandem. The deployment of Darktrace’s platform is flexible—with nine different deployment options, including physical on-premises, virtual, cloud, and hybrid.” (1)

With flexible deployment options, Darktrace offers security teams the ability to choose a model that works best for their organization, ensuring that security doesn’t have to be a “one-size-fits-all” approach.

Conclusion: Why Darktrace / OT stands out in Omdia’s evaluation

Omdia’s 2025 Market Radar for OT Cybersecurity Platforms provides a technical-first, vendor-agnostic evaluation, offering critical insights for organizations looking to strengthen their OT security posture. Darktrace’s recognition as a Market Leader reinforces its unique AI-driven approach, flexible deployment options, and advanced risk management capabilities as key differentiators in an evolving threat landscape.

By leveraging Self-Learning AI, autonomous response, and real-world risk analysis, Darktrace / OT enables organizations to detect, investigate, and mitigate threats before they escalate, without compromising operational uptime.

Read the full report here!

References

  1. www.darktrace.com/resources/darktrace-named-a-market-leader-in-the-2025-omdia-market-radar-for-ot-cybersecurity-platforms
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About the author
Pallavi Singh
Product Marketing Manager, OT Security & Compliance

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Cloud

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April 2, 2025

Fusing Vulnerability and Threat Data: Enhancing the Depth of Attack Analysis

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Cado Security, recently acquired by Darktrace, is excited to announce a significant enhancement to its data collection capabilities, with the addition of a vulnerability discovery feature for Linux-based cloud resources. According to Darktrace’s Annual Threat Report 2024, the most significant campaigns observed in 2024 involved the ongoing exploitation of significant vulnerabilities in internet-facing systems. Cado’s new vulnerability discovery capability further deepens its ability to provide extensive context to security teams, enabling them to make informed decisions about threats, faster than ever.

Deep context to accelerate understanding and remediation

Context is critical when understanding the circumstances surrounding a threat. It can also take many forms – alert data, telemetry, file content, business context (for example asset criticality, core function of the resource), and risk context, such as open vulnerabilities.

When performing an investigation, it is common practice to understand the risk profile of the resource impacted, specifically determining open vulnerabilities and how they may relate to the threat. For example, if an analyst is triaging an alert related to an internet-facing Webserver running Apache, it would greatly benefit the analyst to understand open vulnerabilities in the Apache version that is running, if any of them are exploitable, whether a fix is available, etc. This dataset also serves as an invaluable source when developing a remediation plan, identifying specific vulnerabilities to be prioritised for patching.

Data acquisition in Cado

Cado is the only platform with the ability to perform full forensic captures as well as utilize instant triage collection methods, which is why fusing host-based artifact data with vulnerability data is such an exciting and compelling development.

The vulnerability discovery feature can be run as part of an acquisition – full or triage – as well as independently using a fast ‘Scan only’ mode.

Figure 1: A fast vulnerability scan being performed on the acquired evidence

Once the acquisition has completed, the user will have access to a ‘Vulnerabilities’ table within their investigation, where they are able to view and filter open vulnerabilities (by Severity, CVE ID, Resource, and other properties), as well as pivot to the full Event Timeline. In the Event Timeline, the user will be able to identify whether there is any malicious, suspicious or other interesting activity surrounding the vulnerable package, given the unified timeline presents a complete chronological dataset of all evidence and context collected.

Figure 2: Vulnerabilities discovered on the acquired evidence
Figure 3: Pivot from the Vulnerabilities table to the Event Timeline provides an in-depth view of file and process data associated with the vulnerable package selected. In this example, Apache2.

Future work

In the coming months, we’ll be releasing initial versions of highly anticipated integrations between Cado and Darktrace, including the ability to ingest Darktrace / CLOUD alerts which will automatically trigger a forensic capture (as well as a vulnerability discovery) of the impacted assets.

To learn more about how Cado and Darktrace will combine forces, request a demo today.

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About the author
Paul Bottomley
Director of Product Management, Cado
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